Targeted therapies are effective cancer treatments when accompanied by accurate diagnostic tests that can help identify patients that will respond to those therapies. The YAP/TAZ-TEAD axis is activated and plays a causal role in several cancer types, and TEAD inhibitors are currently in early phase clinical trials in cancer patients. However, mutations that predict YAP/TAZ-TEAD activation are not commonly found in most cancer types, making it hard to determine which tumors are de-pendent upon YAP/TAZ-TEAD. Here, we used a combination of RNA-seq and bioinformatics analysis of metastatic melanoma cells to develop a YAP/TAZ gene signature. We found that the genes in this signature are TEAD-dependent, and that their expression strongly correlates with YAP/TAZ activation in human melanomas. Using DepMap dependency data, we found that this YAP/TAZ signature was predictive of melanoma cell dependence upon YAP/TAZ or TEADs. Importantly, this was not limited to melanoma because this signature was also predictive when tested on a panel of over 1000 cancer cell lines representing numerous distinct cancer types. Our results suggest that YAP/TAZ gene signatures like ours may be an effective tool to predict tumor cell sensitivity to YAP/TAZ-TEAD inhibition, and thus provide a means to identify patients likely to benefit from TEAD inhibitors.